class_docstr: The layer that switches two of the blob dimensions,
  moving the data inside accordingly.
  
  :param input_layer: The input layer and the number of its output. If no number
      is specified, the first output will be connected.
  :type input_layer: object, tuple(object, int)
  :param first_dim: One of the dimensions that should be switched.   
  :type first_dim: str, {"batch_length", "batch_width", "list_size", 
                  "height", "width", "depth", "channels"}
  :param second_dim: The other dimension that should be switched.
  :type second_dim: str, {"batch_length", "batch_width", "list_size", 
                  "height", "width", "depth", "channels"}
  :param name: The layer name.
  :type name: str, default=None
  
  .. rubric:: Layer inputs:
  
  (1) a data blob to be transposed, of any size.
  
  .. rubric:: Layer outputs:
  
  (1) the result of transposition.
docstr: Gets the second dimension to be switched.
          
docstr_tok: ["Gets","the","second","dimension","to","be","switched","."]
code: def second_dim(self):
      """Gets the second dimension to be switched."""
      return self.dimensions[self._internal.get_second_dim()]
  
file_path: neoml/NeoML/Python/neoml/Dnn/Transpose.py
imports: import neoml.PythonWrapper
  from .Dnn import Layer
  from neoml.Utils import check_input_layers
label_desc: Use image node_id 4 for calling the Transpose obj's underlying member method code with example usage: obj.second_dim() and returns: self